Machine and Deep Learning applied to galaxy morphology-A comparative study
Morphological classification is a key piece of information to define samples of galaxies
aiming to study the large-scale structure of the universe. In essence, the challenge is to build …
aiming to study the large-scale structure of the universe. In essence, the challenge is to build …
Twenty-first-century statistical and computational challenges in astrophysics
ED Feigelson, RS De Souza… - Annual Review of …, 2021 - annualreviews.org
Modern astronomy has been rapidly increasing our ability to see deeper into the Universe,
acquiring enormous samples of cosmic populations. Gaining astrophysical insights from …
acquiring enormous samples of cosmic populations. Gaining astrophysical insights from …
A machine learning based morphological classification of 14,245 radio agns selected from the best–heckman sample
Z Ma, H Xu, J Zhu, D Hu, W Li, C Shan… - The Astrophysical …, 2019 - iopscience.iop.org
We present a morphological classification of 14,245 radio active galactic nuclei (AGNs) into
six types, ie, typical Fanaroff–Riley Class I/II (FRI/II), FRI/II-like bent-tailed, X-shaped radio …
six types, ie, typical Fanaroff–Riley Class I/II (FRI/II), FRI/II-like bent-tailed, X-shaped radio …
Galaxy morphology classification using automated machine learning
M Reza - Astronomy and Computing, 2021 - Elsevier
In this paper, we apply five different machine learning algorithms to classify samples into
four categories—spirals, ellipticals, mergers and stars (don't know) using data from the …
four categories—spirals, ellipticals, mergers and stars (don't know) using data from the …
Photometry of high-redshift blended galaxies using deep learning
A Boucaud, M Huertas-Company… - Monthly Notices of …, 2020 - academic.oup.com
The new generation of deep photometric surveys requires unprecedentedly precise shape
and photometry measurements of billions of galaxies to achieve their main science goals. At …
and photometry measurements of billions of galaxies to achieve their main science goals. At …
Forging new worlds: high-resolution synthetic galaxies with chained generative adversarial networks
L Fussell, B Moews - Monthly Notices of the Royal Astronomical …, 2019 - academic.oup.com
Astronomy of the 21st century increasingly finds itself with extreme quantities of data. This
growth in data is ripe for modern technologies such as deep image processing, which has …
growth in data is ripe for modern technologies such as deep image processing, which has …
Synergies between low-and intermediate-redshift galaxy populations revealed with unsupervised machine learning
The colour bimodality of galaxies provides an empirical basis for theories of galaxy
evolution. However, the balance of processes that begets this bimodality has not yet been …
evolution. However, the balance of processes that begets this bimodality has not yet been …
[HTML][HTML] Evaluation metrics for galaxy image generators
A major problem with deep generative models is verifying that the generated distribution
resembles the target distribution while the individual generated sample is indistinguishable …
resembles the target distribution while the individual generated sample is indistinguishable …
Makine öğrenmesi algoritmalarıyla astronomik gözlem kalitesi tahminine yönelik karar destek sistemi geliştirilmesi ve uygulanması
ÖÇ Yavuz, E Karaman, C Yeşilyaprak - Trends in Business and …, 2022 - dergipark.org.tr
Kurulumunun tamamlanmasıyla birlikte araştırmacıların kullanımına sunulması planlanan
Doğu Anadolu Gözlemevi (DAG) teleskobunun etkin ve verimli kullanımı önem arz …
Doğu Anadolu Gözlemevi (DAG) teleskobunun etkin ve verimli kullanımı önem arz …
Reproducible k-means clustering in galaxy feature data from the GAMA survey
ABSTRACT A fundamental bimodality of galaxies in the local Universe is apparent in many
of the features used to describe them. Multiple sub-populations exist within this framework …
of the features used to describe them. Multiple sub-populations exist within this framework …